Preprint
Machine Learning

Security and privacy in 6G networks: New areas and new challenges

Minghao Wang(University of Technology Sydney), Tianqing Zhu(University of Technology Sydney), Tao Zhang(University of Technology Sydney), Jun Zhang(Swinburne University of Technology), Shui Yu(University of Technology Sydney), Wanlei Zhou(University of Technology Sydney)
July 15, 2020Digital Communications and Networks363 citations
PDFDOI

363

Citations

15

Influential Citations

Digital Communications and Networks

Venue

2020

Year

Abstract

With the deployment of more and more 5g networks, the limitations of 5g networks have been found, which undoubtedly promotes the exploratory research of 6G networks as the next generation solutions. These investigations include the fundamental security and privacy problems associated with 6G technologies. Therefore, in order to consolidate and solidify this foundational research as a basis for future investigations, we have prepared a survey on the status quo of 6G security and privacy. The survey begins with a historical review of previous networking technologies and how they have informed the current trends in 6G networking. We then discuss four key aspects of 6G networks – real-time intelligent edge computing, distributed artificial intelligence, intelligent radio, and 3D intercoms – and some promising emerging technologies in each area, along with the relevant security and privacy issues. The survey concludes with a report on the potential use of 6G. Some of the references used in this paper along and further details of several points raised can be found at: security-privacyin5g-6g.github.io.

Analysis

Why This Paper Matters

As 5G networks continue to be deployed, their limitations are becoming apparent, prompting exploratory research into 6G as the next generation of wireless technology. Security and privacy are fundamental concerns for 6G, given its envisioned reliance on advanced technologies such as artificial intelligence, edge computing, and intelligent radio. This paper provides a timely survey that consolidates the status quo of 6G security and privacy research, offering a structured overview that can guide future investigations.

The survey is significant because it bridges the gap between historical networking trends and the emerging challenges of 6G. By reviewing previous networking technologies and their security lessons, the authors contextualize the new threats that 6G may face. This historical perspective is crucial for understanding how security and privacy requirements evolve with each generation and for anticipating the unique vulnerabilities introduced by 6G's key technologies.

Moreover, the paper's focus on four key aspects—real-time intelligent edge computing, distributed artificial intelligence, intelligent radio, and 3D intercoms—highlights the multidisciplinary nature of 6G security. These areas are not only central to 6G's functionality but also introduce novel attack surfaces and privacy risks. By identifying these issues early, the survey helps the research community prioritize and address them proactively.

Technical Contributions

  • Historical review of networking technologies: The paper traces the evolution of security and privacy concerns from earlier generations to 6G, providing a foundation for understanding current trends.
  • Four key aspects of 6G: The survey identifies and discusses real-time intelligent edge computing, distributed artificial intelligence, intelligent radio, and 3D intercoms as critical areas for 6G security and privacy.
  • Emerging technologies and security issues: Within each aspect, the authors examine promising technologies (e.g., edge AI, federated learning, intelligent spectrum management) and their associated security and privacy challenges.
  • Potential use cases: The survey concludes with a report on potential applications of 6G, linking security requirements to practical scenarios.
  • Online resource: The authors provide additional details and references at a dedicated website, enhancing the survey's utility.

Results

As a survey paper, this work does not present experimental results or quantitative metrics. Instead, it offers a qualitative synthesis of existing literature, identifying security and privacy issues and outlining open research directions. The paper's value lies in its comprehensive coverage and structured analysis, which can serve as a reference for future studies. The authors do not compare different solutions or provide performance benchmarks, which is typical for survey papers.

Significance

The survey's significance lies in its foundational role for 6G security and privacy research. By systematically categorizing challenges across four key technological domains, it provides a roadmap for researchers and practitioners. The paper's historical context helps in understanding the evolution of security threats and the need for new paradigms. Additionally, by highlighting open issues, it stimulates further research and development in securing 6G networks. Given the increasing reliance on AI and edge computing in 6G, the survey's insights are particularly relevant to the AI community, emphasizing the need for secure and privacy-preserving AI in next-generation networks. The paper has been widely cited, indicating its impact on shaping the discourse around 6G security.

6g-networkssecurityprivacyedge-computingdistributed-aiintelligent-radiosurvey

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